def plotMol(pdb,filename):
pdbName = reformatPDB(pdb,1)
mol = Chem.MolFromPDBFile(pdbName,removeHs=False,sanitize=False)
os.remove(pdbName)
# AllChem.GenerateDepictionMatching2DStructure(mol,refMol)
opt = Draw.DrawingOptions()
opt.bgColor=None
Draw.MolToFile(mol,filename,kekulize=False,options=opt)
def defaultDrawOptions():
'''This function returns an RDKit drawing options object with
default drawing options.'''
opts = Draw.DrawingOptions()
# opts.elemDict = defaultdict(lambda: (0,0,0)) # all atoms are black
opts.noCarbonSymbols = True
opts.selectColor = (1, 0, 0)
opts.wedgeBonds = True
return opts
def defaultDrawOptions():
"""Returns an RDKit drawing options object with default drawing options."""
opts = Draw.DrawingOptions()
# opts.elemDict = defaultdict(lambda: (0,0,0)) # all atoms are black
opts.noCarbonSymbols = True
opts.selectColor = (1, 0, 0)
opts.wedgeBonds = True
opts.elemDict = defaultdict(lambda: (0, 0, 0))
opts.dotsPerAngstrom = 20
opts.bondLineWidth = 1.5
atomLabelFontFace = 'arial'
return opts
def testSpecialCases(self):
options = Draw.DrawingOptions()
options.atomLabelDeuteriumTritium = True
self._testMolToImage(mol=Chem.MolFromSmiles('[2H][C@]([3H])(C)F'), options=options)
# shared rings
self._testMolToImage(mol=Chem.MolFromSmiles('c1cccc2cc(cccc3)c3cc21'))
self._testMolToImage(mol=Chem.MolFromSmiles('C1=CC=CC=CC=C1'))
self._testMolToImage(mol=Chem.MolFromSmiles('C=C=C'))
self._testMolToImage(mol=Chem.MolFromSmiles('CC#N'), showImage=False)
self._testMolToImage(mol=Chem.MolFromSmiles('[CH2-][C-2]C[CH3+][CH5+2]'))
self._testMolToImage(mol=Chem.MolFromSmiles('[Na+].[OH-]'))
self._testMolToImage(mol=Chem.MolFromSmiles('c1ccccc1c1ccccc1'),
highlightAtoms=(0, 1, 2, 3, 4, 5, 6))
self._testMolToImage(mol=Chem.MolFromSmiles('c1ccccc1c1ccccc1'),
highlightBonds=(0, 2, 4, 6, 8, 10))
self._testMolToImage(mol=Chem.MolFromSmiles('c1ccccc1c1ccc(cc1)c1ccc(cc1)c1ccc(cc1)'))
def Convert(self, prop, **kwargs):
"""
Converts MOL structure into SVG image.
Args:
prop: pyeds.PropertyValue
Property to convert.
Returns:
image: str or None
SVG image data.
"""
# check value
if not prop.Value:
return None
# try to convert into RDKit object
try:
from rdkit.Chem import AllChem
from rdkit.Chem import Draw
mol = AllChem.MolFromMolBlock(prop.Value)
except ImportError:
return None
# get image path
filename = "%s.%s" % (str(uuid.uuid4()), "svg")
path = os.path.join(tempfile.gettempdir(), filename)
# set drawing options
options = Draw.DrawingOptions()
options.bgColor = None
options.defaultColor = (0, 0, 0)
options.colorBonds = False
options.coordScale = 1.0
# make image
Draw.MolToFile(mol, path, size=(120, 75), options=options, fitImage=False, ignoreHs=True)
# read image data
with open(path) as svg_file:
svg = svg_file.read()
# delete file
os.remove(path)
return svg
def _CairoDrawer(self, rdmol):
"""Render an svg using cairo or agg renderer."""
# Some drawing options
options = Draw.DrawingOptions()
options.bondLineWidth = 1
# Prepare drawing
useAGG, useCairo, Canvas = Draw._getCanvas()
canvas = Canvas(size=(self.width, self.height),
imageType='svg',
fileName=self.svgfile)
drawer = Draw.MolDrawing(canvas=canvas, drawingOptions=options)
drawer.AddMol(rdmol)
if self.legend is not None:
from rdkit.Chem.Draw.MolDrawing import Font
pos = (self.width / 2, int(.1 * self.height), 0)
font = Font(face='serif', size=18)
canvas.addCanvasText(self.legend, pos, font)
canvas.flush()
data_new = data_new.drop(['ID'],axis = 1)
data_new.index = range(len(data_new))
data_new.to_csv(r"C:\Users\86136\Desktop\result\RNN_weight" +'\\'+str(i)+'_new_weight.csv')
###################################################################################################
####画图，画出每个化合物的前10个重要元素
from rdkit import Chem
from rdkit.Chem import AllChem
from rdkit.Chem import Draw
from rdkit.Chem import PandasTools
import pandas as pd
data_csv= pd.read_csv(r"C:\Users\86136\Desktop\CYSLTR1_DATA\CYSLT1_standerd_database.csv")
Chem.PandasTools.AddMoleculeColumnToFrame(data_csv, smilesCol='SMILES', molCol='MOL', includeFingerprints=True)
opts = Draw.DrawingOptions()
opts.elemDict = {1: (0, 0, 0),
7: (0, 0, 0),
8: (0, 0, 0),
9: (0, 0, 0),
15: (0, 0, 0),
16: (0, 0, 0),
17: (0, 0, 0),
35: (0, 0, 0),
53: (0, 0, 0),
0: (0, 0, 0)}
for i in range(len(data_csv)):
if data_csv['new_value'][i] == 1:
#每一个化合物的attention weight
from rdkit import Chem
from rdkit.Chem import Draw
from rdkit.Chem.Draw import rdDepictor, SimilarityMaps
def RobustSmilesMolSupplier(filename):
with open(filename) as f:
for line in f:
words = line.split()
smile = words[0]
name = " ".join(words[1:]) # everything after the SMILES string
yield (name, Chem.MolFromSmiles(smile))
# draw all atoms in black
drawOptions = Draw.DrawingOptions()
drawOptions.elemDict = {}
drawOptions.bgColor = None
if __name__ == '__main__':
if len(sys.argv) != 3:
print("usage: %s molecules.smi molecules.delta" % sys.argv[0])
exit(1)
smiles_fn = sys.argv[1]
deltas_fn = sys.argv[2]
delta_max = 0.1 # arbitrary, to normalize deltas and color-scale them
delta_file = open(deltas_fn, 'r')
count = 0
for long_name, mol in RobustSmilesMolSupplier(smiles_fn):
# split by '_' in case name was postfixed with underscores
# and additional data
